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Plasmo.jl - Platform for Scalable Modeling and Optimization

Plasmo.jl is a graph-based optimization framework written in Julia that builds upon the JuMP.jl modeling language to offer a modular style to construct and solve optimization problems. The package implements what is called an OptiGraph abstraction to create graph-structured optimization models and facilitate graph-based processing functions. An OptiGraph captures the underlying graph topology of an optimization problem using OptiNodes (which represent stand-alone self-contained optimization models) that are coupled by means of OptiEdges (which represent coupling constraints). The resulting topology can be used for tasks such as visualization, graph partitioning, and interfacing (and developing) decomposition-based solvers.

Installation

Plasmo.jl works for Julia versions 1.6 and later. From Julia, Plasmo.jl can be installed using the Pkg module:

import Pkg
Pkg.add("Plasmo")

or alternatively from the Julia package manager by performing the following:

pkg> add Plasmo

Contents

Future Development

There are currently a few major development avenues for Plasmo.jl. Here is a list of some of the major features we intend to add for future releases:

  • Distributed modeling capabilities
  • Custom optigraph partitioning algorithms
  • Decomposition-based solver development
  • GraphOptInterface.jl development
  • Interface with InfiniteOpt.jl

We are also looking for help from new contributors. If you would like to contribute to Plasmo.jl, please create a new issue or pull request on the GitHub page

Index

Citing Plasmo.jl

If you find Plasmo.jl useful for your work, we ask that you cite the manuscript:

@article{Jalving2022,
  author = {Jalving, Jordan and Shin, Sungho and Zavala, Victor M.},
  title = {A graph-based modeling abstraction for optimization: concepts and implementation in {Plasmo.jl}},
  journal = {Mathematical Programming Computation},
  volume = {14},
  pages = {699--747},
  year = {2022},
  doi = {10.1007/s12532-022-00223-3}
}

You can access an earlier pre-print of this article.

There is also an earlier manuscript where we presented the initial ideas behind Plasmo.jl which you can find here:

@article{JalvingCaoZavala2019,
author = {Jalving, Jordan and Cao, Yankai and Zavala, Victor M},
journal = {Computers {\&} Chemical Engineering},
pages = {134--154},
title = {Graph-based modeling and simulation of complex systems},
volume = {125},
year = {2019},
doi = {10.1016/j.compchemeng.2019.03.009}
}

A pre-print of this paper can also be found here